• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.274-279
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• 2017

LCD(Liquid Crystal Display) panel cutting problem is a sort of two dimensional cutting stock problem. A cutting stock problem is problem that it minimizes the loss of the stock when a stock is cut into various parts. In the most research of the two dimensional cutting stock problem, it is supposed that the relative angle of a stock and parts is not important. Usually the angle is regarded as horizontal or perpendicular. In the manufacturing of polarizing film of LCD, the relative angle should be maintained at some specific angle because of the physical and/or chemical characteristics of raw material. We propose a mathematical model for solving this problem, a two-dimensional non-Guillotine cutting stock problem that is restricted by an arranged angle. Some example problems are solved by the C++ program using ILOG CPLEX classes. We could get the verification and validation of the suggested model based on the solutions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.276-279
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• 1996

This paper deals with the method providing an exact solution to the 3-dimensional guillotine cutting stock problem. We suggest a 3-stage sutting method using the property that cubic material has to be cut into 2-dimensional planes firstly. This method requires more stocks that the general guillotine cutting methods but can save work force. By using the 1-dimensional dynamic programming, we reduce the computational time and the memory requirement in the 3-stage guillotine cutting method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.35
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• pp.47-52
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• 1995

The aim of this paper is to suggest the cutting stock problems which are two-dimensional in form, but can be treated as the optimization methods for one-dimensional cutting stock problem by exploiting the length requirement of the products. The solution method consists of two stages. The first calculates the number of roll pieces of each size. Next, 1-dimensional cutting stock model is set up. One heuristic method to calculate the number of each roll is suggested. The trim loss minization criteria are used to design the objective function. This model can be solved by the conventional cutting stock procedures based on enumerating the possible cutting patterns.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.741-751
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• 1996

The three dimensional cutting-stock problem is to maximize the total value of pieces which are smaller cubics-cut from a original cubic stock. This paper suggests a method to maximize the total value of different size cut pieces using the orthogonal non-guillotine cut technique. We first formulated a zero-one integer programming, then developed a Lagrangeon relaxation method far the problem. The solutions were given by using a brunch-end-bound technique associates with Lagrangean relaxation, which guarantees an optimal solution.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.424-431
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• 2001

This paper is concerned with the unconstrained two-dimensional cutting problem of cutting small rectangles (products), each of which has its own profit and size, from a large rectangle (material) to maximize the profit-sum of products. Since this problem is used as a sub-problem to generate a cutting pattern in the algorithms for the two-dimensional cutting stock problem, most of researches for the two-dimensional cutting stock problem have been concentrated on solving this sub-problem more efficiently. This paper improves Hifi and Zissimopoulos's recursive algorithm, which is known as the most efficient exact algorithm, by applying newly proposed upper bound and searching strategy. The experimental results show that the proposed algorithm has been improved significantly in the computational amount of time as compared with the Hifi and Zissimopulos's algorithm.

• IE interfaces
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• v.8 no.2
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• pp.151-159
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• 1995

Two-dimensional cutting stock problem is to find a waste-minimizing method of cutting a single rectangular plane into a number of smaller pieces of known dimensions. In practice, besides wastes, setup cost taken during adjusting is of an important concern. We suggest 2-phased guillotine cutting method as a solution to the problem which minimize wastes and setup costs. Also, in order to reduce the computing time we apply techniques of discretization, cutoff, median. Experimental results show good performance of our algorithm.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.13-18
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• 2010

The composite stock cutting problem is defined as allocating rectangular and irregular patterns onto a large composite stock sheet of finite dimensions in such a way that the resulting scrap will be minimized. In this paper, we introduce a novel approach to hybrid optimization algorithm called MGA in MPI (Message Passing Interface) environments. The proposed MGA combines the benefit of rapid convergence property of Mean Field Annealing and the effective genetic operations. This paper also proposes the efficient data structures for pattern related information.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.1-8
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• 2009

In this paper, we deal an implementation of the software that produces sub-optimal solution of cutting-ironbar planning problem using dynamic programming. Generally, it is required to design an optimization algorithm to accept the practical requirements of cutting ironbar manufacturing. But, this problem is a multiple-sized 1-dimensional cutting stock problem and Linear Programming approaches to get the optimal solution is difficult to be applied due to the problem of explosive computation and memory limitation. In order to overcome this problem, we reform the problem for applying Dynamic Programming and propose a cutting-ironbar planning algorithm searching the sub-optimal solution in the space of fixed amount of combinated columns by using heuristics. Then, we design a graphic user interfaces and screen displays to be operated conveniently in the industry workplace and implement the software using open-source GUI library toolkit, GTK+.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.20-29
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• 2002

The composite stock cutting problem is to allocate rectangular and/or irregular patterns onto a large composite stock sheet of finite dimensions in such a way that the resulting scrap will be minimized. In this paper, the distributed simulated annealing with the new cost error tolerant spatial decomposition is applied to the composite stock cutting problem in MPI environments. The cost error tolerant scheme relaxes synchronization and chooses small perturbations on states asynchronously in a dynamically changed stream length to keep the convergence property of the sequential annealing. This paper proposes the efficient data structures for representation of patterns and their affinity relations and also shows how to determine move generations, annealing parameters, and a cost function. The spatial decomposition method is addressed in detail. This paper identifies that the final quality is not degraded with almost linear speedup. Composite stock shapes are not constrained to convex polygons or even regular shapes, but the rotations are only allowed to 2 or 4 due to its composite nature.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.30-39
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• 2010

This paper considers a problem of optimizing torch paths to cut stock plates nested with open contours. For each contour, one of the two ending points is to be selected as a starting point of cutting with the other being the exit point. A torch path is composed of a single depot and a series of starting and ending points of contours to be cut. The torch path optimization problem is shown to be formulated as an extended version of the standard travelling salesman problem. To solve the problem, a hybrid genetic algorithm with the local search of torch paths is proposed. The genetic algorithm is tested for hypothetical problems whose optimal solutions are known in advance due to the special structure of them. The computational results show that the algorithm generates very near optimal solutions for most cases of the test problems, which verifies the validity of the algorithms.